Increase the value of a column based on values in another column-CodePudding

I am trying to increase the price of on the red pens in this example by 10%. Below is what I have have tried but it increases all the prices once it finds a match

import pandas as pd


df = pd.DataFrame({'item':['red ballpoint pen','red felt tip pen', 'blue ballpoint pen','red eraser',],
                   'price':[1.50,2.00,1.50,.50]})
for x in df['item']:

if 'red' in x and 'pen' in x:
    df['price'] =  df['price']*.10   df['price']

I can filter the item column and get the pens but I cannot figure out how to update the price in place without increasing the price on all items

Any help would be greatly appreciated

CodePudding user response：

This will use np.where() to find where both pen and red exist

df['price'] = np.where((df['item'].str.contains('red')) & (df['item'].str.contains('pen')), df['price'] * 1.10, df['price'])
df

CodePudding user response：

Use loc and str.contains:

m = df['item'].str.contains('red') & df['item'].str.contains('pen')
df.loc[m, 'price'] *= 1.10

CodePudding user response：

You can just use pandas to do this in a oneliner:

df.loc[df.item.str.contains('pen') & df.item.str.contains('red'), 'price'] *= 1.1